Baltic Women`s Volleyball League 2019-2020

Baltic Women`s Volleyball League 2019-2020

Baltic Women`s Volleyball League 2019-2020 Best players SETTER
PlayerPlayed
  MatchesSetsSetter Efficiency
('#' - '/' - '=') / TOT

1

Vaitkutė Evelina
(TK Aušrinė-KKSC)

1

1

50.00%
(2 - 0 - 0) / 4

2

Kaur Laura
(Audentes SG/NK)

2

6

42.86%
(3 - 0 - 0) / 7

3

Bahmatšev Kaisa
(TalTech/Tradehouse)

4

10

38.18%
(29 - 6 - 2) / 55

4

Ignatjeva Sofija Anastasija
(RVS)

7

14

36.67%
(15 - 2 - 2) / 30

5

Mõnnakmäe Julija
(TalTech/Tradehouse)

11

29

34.33%
(98 - 10 - 19) / 201

6

Starkopf Ann
(TÜ/Bigbank)

5

10

34.29%
(18 - 2 - 4) / 35

7

Reknere Elza
(RVS)

16

64

29.15%
(275 - 40 - 56) / 614

8

Noormets Liis
(TÜ/Bigbank)

15

58

28.87%
(203 - 29 - 38) / 471

9

Zablotska Khrystyna
(TK “Kaunas”-VDU)

1

3

28.57%
(7 - 1 - 2) / 14

10


()

4

17

25.86%
(48 - 7 - 11) / 116

11

Dolotova Elvita
(Jelgava/LLU)

16

64

25.11%
(192 - 43 - 37) / 446

12

Kuts Vera
(TK “Kaunas”-VDU)

17

50

23.91%
(111 - 22 - 23) / 276

13

Atapovič Viktoryia
(Alytaus “Prekyba – Parama”)

12

39

22.36%
(101 - 17 - 29) / 246

14

Valionytė Vaiva
(TK Aušrinė-KKSC)

1

4

22.22%
(8 - 1 - 3) / 18

15

Šiūšaitė Liepa
(TK Aušrinė-KKSC)

14

48

21.57%
(129 - 29 - 26) / 343

16

Kalabura Tetiana
(Alytaus “Prekyba – Parama”)

6

19

19.61%
(58 - 11 - 17) / 153

17

Pravdinskaitė Karolina
(TK “Kaunas”-VDU)

20

63

19.12%
(102 - 26 - 24) / 272

18

Vesna Irina
(VK "miLATss")

12

49

18.79%
(174 - 47 - 43) / 447

19

Varlõgina Melissa
(TalTech/Tradehouse)

9

21

17.12%
(53 - 10 - 18) / 146

20

Loos Helena
(Audentes SG/NK)

8

20

16.79%
(47 - 11 - 14) / 131

21

Sebekina Anastasija
(Alytaus “Prekyba – Parama”)

4

13

14.29%
(15 - 2 - 7) / 42

22

Matseichyk Natallia
(Alytaus “Prekyba – Parama”)

1

4

14.29%
(3 - 0 - 2) / 7

23

Sebežiova Akvile
(Alytaus “Prekyba – Parama”)

14

52

13.36%
(178 - 57 - 53) / 509

24

Švarca Alise
(Jelgava/LLU)

14

29

9.23%
(22 - 7 - 9) / 65

25

Kibbermann Karolina
(Audentes SG/NK)

11

33

7.65%
(59 - 15 - 30) / 183

Ranking Calculation

Setter

This ranking is based on Setter data for each player with a minimum of 1 played matches and at least 10% of all sets of the team.